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DIGITAL SIGNAL PROCESSING (DSP) 197
Here are some further descriptions of the Sampling Theorem:
http://ccrma-www.stanford.edu/ jos/r320/Shannon_s_Sampling_
Theorem.html
http://ptolemy.eecs.berkeley.edu/eecs20/week13/nyquistShannon.html
www.hsdal.ufl.edu/Projects/IntroDSP/Notes/Sampling%20Theorem
%20Brief.doc
If you want to have some fun with language, take a look at the www.nightgarden
.com/shannon.htm web site.
With such great theorists like Nyquist and Shannon being brought up, I feel odd
about injecting some practical details into this discussion (see Figure 8-4). Unfortu-
nately, it has to be done. The world is a tough place, Grasshopper, and one cannot go
about spouting generalities without getting in trouble. So hold your nose; here comes
some castor oil!
DSP is all about transforming data so it can be processed and used to good effect.
The trouble is, most of the transformations distort the data along the way. Before we
even get started with DSP, we find that the antialias filters and the A/D both alter the
data in ways that must be carefully taken into account. Further, once the DSP proces-
sor and the D/A come into play, we will see that they too distort the data.
It’s all very easy to slap an A/D and a D/A onto a computer and call it a DSP system.
The difficulty comes in making it see the world correctly and helping it make the right
decisions. So here are some of the salient details that should be taken into account.

FIGURE 8-4 Nyquist and Shannon